{"title":"用于预测建模的增强集成模型:一个概念框架","authors":"Janson Luke Ong Wai Kit, V. Asirvadam, M. Hassan","doi":"10.1109/CSPA52141.2021.9377299","DOIUrl":null,"url":null,"abstract":"Ensemble Model learnings refers to a collection of techniques that combine multiple learning algorithms to improve overall prediction accuracy and persistency. This paper looks into the conceptual framework of how to enhance the ensemble model techniques and provide a comprehensive study on predictive model approach using an enhanced ensemble model. We explore the framework, performance evaluation and experimental approach.","PeriodicalId":194655,"journal":{"name":"2021 IEEE 17th International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Enhanced Ensemble Models for Predictive Modeling: A Conceptual Framework\",\"authors\":\"Janson Luke Ong Wai Kit, V. Asirvadam, M. Hassan\",\"doi\":\"10.1109/CSPA52141.2021.9377299\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ensemble Model learnings refers to a collection of techniques that combine multiple learning algorithms to improve overall prediction accuracy and persistency. This paper looks into the conceptual framework of how to enhance the ensemble model techniques and provide a comprehensive study on predictive model approach using an enhanced ensemble model. We explore the framework, performance evaluation and experimental approach.\",\"PeriodicalId\":194655,\"journal\":{\"name\":\"2021 IEEE 17th International Colloquium on Signal Processing & Its Applications (CSPA)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 17th International Colloquium on Signal Processing & Its Applications (CSPA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSPA52141.2021.9377299\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 17th International Colloquium on Signal Processing & Its Applications (CSPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSPA52141.2021.9377299","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhanced Ensemble Models for Predictive Modeling: A Conceptual Framework
Ensemble Model learnings refers to a collection of techniques that combine multiple learning algorithms to improve overall prediction accuracy and persistency. This paper looks into the conceptual framework of how to enhance the ensemble model techniques and provide a comprehensive study on predictive model approach using an enhanced ensemble model. We explore the framework, performance evaluation and experimental approach.